ADAPTIVE WAVELETS SLIDING MODE CONTROL FOR A CLASS OF SECOND ORDER UNDERACTUATED MECHANICAL SYSTEMS

The control of underactuated mechanical systems (UMS) remains an attracting field where researchers can develop their control algorithms. To this date, various linear and nonlinear control techniques using classical and intelligent methods have been published in literature. In this work, an adaptive controller using sliding mode control (SMC) and wavelets network (WN) is proposed for a class of second-order UMS with two degrees of freedom (DOF).This adaptive control strategy takes advantage of both sliding mode control and wavelet properties. In the main result, we consider the case of un-modeled dynamics of the above-mentioned UMS, and we introduce a wavelets network to design an adaptive controller based on the SMC. The update algorithms are directly extracted by using the gradient descent method and conditions are then settled to achieve the required convergence performance.The efficacy of the proposed adaptive approach is demonstrated through an application to the pendubot

Comparative Study of Takagi-Sugeno-Kang and Madani Algorithms in Type-1 and Interval Type-2 Fuzzy Control for Self-Balancing Wheelchairs

This study examines the effectiveness of four different fuzzy logic controllers in self-balancing wheelchairs. The controllers under consideration are Type-1 Takagi-Sugeno-Kang (TSK) FLC, Interval Type-2 TSK FLC, Type-1 Mamdani FLC, and Interval Type-2 Mamdani FLC. A MATLAB-based simulation environment serves for the evaluation, focusing on key performance indicators like percentage overshoot, rise time, settling time, and displacement. Two testing methodologies were designed to simulate both ideal conditions and real-world hardware limitations. The simulations reveal distinct advantages for each controller type. For example, Type-1 TSK excels in minimizing overshoot but requires higher force. Interval Type-2 TSK shows the quickest settling times but needs the most force. Type-1 Mamdani has the fastest rise time with the lowest force requirement but experiences a higher percentage of overshoot. Interval Type-2 Mamdani offers balanced performance across all metrics. When a 2.7 N control input cap is imposed, Type-2 controllers prove notably more efficient in minimizing overshoot. These results offer valuable insights for future design and real-world application of self-balancing wheelchairs. Further studies are recommended for the empirical testing and refinement of these controllers, especially since the initial findings were limited to four-wheeled self-balancing robotic wheelchairs

A feasibility study for the development of sustainable theoretical framework for smart air-conditioning

Air-conditioning as a technical solution to protect inhabitants from excessive heat exposure creates the challenge of expanding global warming and climate change. While air-conditioning has mostly been applied as an improvement to living conditions, health and environmental problems associated with its use frequently occur. Therefore, this study challenges and extends existing knowledge on sustainability-related to smart air-conditioning systems, where social, environmental and economic dynamics were considered. For instance, when exploring renewable-based options, advanced smart control techniques and profitability measures of air-conditioning reinforce the three pillars of sustainability. In addition to eradicating indoor health effects, this also helps to combat climate change through the system’s sustainability. As an exercise in conceptual modelling, the principal component analysis accounts for sustainable planning and its integration into the theoretical framework. The newly proposed photovoltaic solar air-conditioning was optimised using Polysun to demonstrate the significant application of solar energy in air-conditioning systems, thereby reducing the level of energy consumption and carbon emissions. The newly proposed fuzzy proportional-integral-derivative controller and backpropagation neural network were optimised using Matlab to control the indoor temperature and CO2 level appropriately. The controller of the indoor environment was designed, and the proportional-integral-derivative control was utilised as a result of its suitability. The smart controllers were designed to regulate the parameters automatically to ensure an optimised control output. The performance of photovoltaic solar air-conditioning in different temperate climates of Rome, Toulouse and London districts achieved a higher coefficient of performance of 3.37, 3.69 and 3.97, respectively. The system saved significant amount of energy and carbon emissions. The indoor temperature and indoor CO2 possess an appropriate time constant and settling time, respectively. The profitability assessment of the system revealed its adequate efficiency with an overall payback period of 5.5 years